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Formal
concept analysis (FCA) is a mathematical tool for
analyzing data and formally representing conceptual
knowledge. FCA helps forming conceptual structures
from data. Such structures consist of units, which
are formal abstractions of concepts of human thought
allowing meaningful and comprehensible interpretation.
FCA is a mathematical discipline whose features include:
1-Visualizing inherent properties in data sets,
2- Interactively exploring attributes of objects and
their corresponding contexts, and
3- Formally classifying systems based on relationships
among objects and attributes through the concept of
mathematical lattices.
As an aside, FCA mathematical settings have recently
been shown to provide a theoretical framework for
the efficient resolution of many practical problems
from data mining, software engineering and information
retrieval.
CLA is an international conference devoted
to both theoretical and applicational aspects of formal
concept analysis (FCA). Papers in the above areas
of interest are solicited:
 foundations
of FCA
mathematical structures related to FCA (concept lattices,
Galois connections, closure structures, attribute
implications)
algorithms
for FCA
relationship
of FCA to other methods of data analysis (clustering,
association rules, classification, etc.)
visualization
of data in FCA
data
for FCA (object-attribute data, preprocessing of data,
conceptual scaling, fuzzy attributes, etc.)
applications
of FCA (knowledge discovery, data mining, information
retrieval, ontology, semantic web, etc.)
Other
related areas
All papers will be judged based on their
technical merits, originality, relevance to areas
of interest of CLA 2006, and presentation clarity.
Papers should describe original work that has not
been published before, is not under review elsewhere,
and will not be submitted elsewhere during CLA 2006's
review period.
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